An Agent-based New Energy Vehicle Distribution Modeling And Simulating Research

Promotion of new energy vehicles is of great importance to energy security, energy conversation and economic growth. Technological learning is considered as an important internal force to promote new energy vehicles which are still very expensive nowadays. As the relationship between new energy vehicles diffusion and their refueling stations construction is just like a "chicken and egg" problem, technological learning of new energy vehicles is hard to start spontaneously. Therefore, promotion of new energy vehicles usually requires governments to establish demonstration projects as seeds of technology learning. Subject to financial constraints, the government can't build widespread and intensive new energy vehicles refueling stations immediately. So how to optimize the initial spatial distribution of refueling station becomes a real problem for promoting new energy vehicles.From the perspective of complex adaptive system, this paper proposes an multi-agent based new energy vehicles diffusion model and develops a platform to simulate diffusion of vehicles and stations. Then take Shanghai as an example, adopt evolutionary algorithm and scenario analysis algorithm to simulate the diffusion results of new energy vehicles and their fuel-filling stations through interaction between drivers of new energy vehicles and new energy providers in pre-set road grids. Finally, to improve decision performance, a method to optimize the initial spatial distribution of new energy vehicles and refueling stations is suggested.